- The model training and testing is replaced by data mining, which works by trying to get useful information from the data.
- New data is included continuously into the data flow, and the full cycle must be fulfilled before feeding it into a machine learning model.
- A hyperparameter value is set before starting the learning process and defines some characteristics of the model (for example, the number of cycles in an artificial neural network training model).
- The following steps can be performed automatically by AutoML:
- Data preprocessing
- Feature engineering
- Model selection
- Optimization of the model hyperparameters
- Analysis of the model results
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